The Foundations for Provenance on the Web

Abstract

Provenance, i.e., the origin or source of something, is becoming an important concern, since it offers the means to verify data products, to infer their quality, to analyse the processes that led to them, and to decide whether they can be trusted. For instance, provenance enables the reproducibility of scientific results; provenance is necessary to track attribution and credit in curated databases; and, it is essential for reasoners to make trust judgements about the information they use over the Semantic Web. As the Web allows information sharing, discovery, aggregation, filtering and flow in an unprecedented manner, it also becomes very difficult to identify, reliably, the original source that produced an information item on the Web. Since the emerging use of provenance in niche applications is undoubtedly demonstrating the benefits of provenance, we contend that provenance can and should reliably be tracked and exploited on the Web, and we survey the necessary foundations to achieve such a vision. Using multiple data sources, we have compiled the largest bibliographical database on provenance so far. This large corpus allows us to analyse emerging trends in the research community. Specifically, using the CiteSpace tool, we identify clusters of papers that constitute research fronts, from which we derive characteristics that we use to structure our foundational framework for provenance on the Web. We note that such an endeavour requires a multidisciplinary approach, since it requires contributions from many computer science sub-disciplines, but also other non-technical fields given the human challenge that is anticipated. To develop our vision, it is necessary to provide a definition of provenance that applies to the Web context. Our conceptual definition of provenance is expressed in terms of processes, and is shown to generalise various definitions of provenance commonly encountered. Furthermore, by bringing realistic distributed systems assumptions, we refine our definition as a query over assertions made by processes. Given that the majority of work on provenance has been undertaken by the database, workflow and e-science communities, we review some of their work, contrasting approaches, and focusing on important topics we believe to be crucial for bringing provenance to the Web, such as abstraction, collections, storage, queries, workflow evolution, semantics and activities involving human interactions. However, provenance approaches developed in the context of databases and workflows essentially deal with closed systems. By that, we mean that workflow or database management systems are in full control of the data they manage, and track their provenance within their own scope, but not beyond. In the context of the Web, a broader approach is required by which chunks of provenance representation can be brought together to describe the provenance of information flowing across multiple systems. This is the specific purpose of the Open Provenance Vision, which is an approach that consists of controlled vocabula...

Using Provenance to Support Good Laboratory Practice in Grid Environments

“…"The provenance of a piece of data is the process that led to that piece of data." [12] Based on this understanding, approaches for identifying provenance use cases for modeling processes and for integrating provenance tracking into applications are developed. Also, concepts to store and visualise provenance information are investigated.…”

“…For this the user can send an archive to an archiving service, to analyses the credibility of the archive. 12 To provide sufficient information, the user can activate a specific script extension, which generates an archive composed of information relevant to the data from information in the provenance store. The user selects a study report, and the provenance store is queried for all data items influencing the report for each step.…”

Explicit Auditing

“…Transparency is an increasing concern in computer systems: for complex systems, whose desired behavior may be difficult to formally specify, auditing is an important complement to traditional techniques for verification and static analysis for security [2,6,12,27,19,16], program slicing [22,26], and provenance [21,24]. However, formal foundations of auditing as a programming language primitive are not yet well-established: most approaches view auditing as an extra-linguistic operation, rather than a first-class construct.…”

Reasoning over Taxonomic Change: Exploring Alignments for the Perelleschus Use Case

“…Over time these changes can result in an imperfect semantic tracking of taxonomic perspectives through varying combinations of valid names and synonyms [1][2][3][11][12]. It is generally recognized that the Linnaean naming system, while serviceable in many regards [13][14][15], is not designed to represent all kinds of taxonomic content change; i.e., to fully track taxonomic provenance [16][17][18]. This circumstance poses different data integration challenges depending on the agents -humans versus computers -and space/time dimensions involved in name-based data transmission.…”